DNA损伤在衰老相关疾病中的研究进展

DNA损伤是衰老相关疾病领域的研究热点, 可引起细胞周期停滞、凋亡, 加快个体衰老速度、增加衰老相关疾病的患病风险。本文将从细胞衰老和个体衰老两个层面阐述其与衰老之间的研究进展, 并综述其与衰老常见相关疾病(肿瘤、心血管疾病、阿尔茨海默病)及早衰综合征的关系, 为抗衰老研究和临床干预衰老相关疾病提供理论依据。     

Care of Seniors with Breast Cancer – Treatment Received and Refining Decision Making

AimsTreatment decisions for older patients with breast cancer are complex and evidence is largely extrapolated from younger populations. Frailty and comorbidity need to be considered. We studied the baseline characteristics and treatment decisions in older patients in Christchurch with breast cancer and assessed survival outcomes and prognostic/discriminatory performance of several tools.Materials and methodsWe searched the Canterbury Breast Cancer Registry and identified patients aged 70 years or older at diagnosis with invasive, non-metastatic breast cancer between 1 June 2009 and 30 June 2015. We retrieved demographics, treatment and outcome information. Overall survival and breast cancer-specific survival were estimated. Tools analysing performance status and comorbidity were assessed for their prognostic and discriminatory power.ResultsIn total, 440 patients were identified. Primary surgery was carried out for 362 patients (82.3%): breast-conserving surgery in 114 (of whom 88.6% received radiation therapy); mastectomy in 248 (of whom 24.6% received radiation). Hormone therapy was given for 265 (71.1%) patients with oestrogen receptor-positive cancers. Two hundred and seventy-four (62.3%) patients received full standard treatment, which was associated with significantly improved 5-year survival and 5-year breast cancer-specific survival. The median estimated overall survival was 8.2 years (95% confidence interval 7.3–9.1 years). Of those who died, 71.3% of deaths were due to causes other than breast cancer or unknown causes. The comorbidity-adjusted life expectancy (CALE) showed partial prognostic accuracy. CALE, Charlson and Eastern Cooperative Oncology Group tools all showed discriminatory value.ConclusionIn this population-based series of older patients with breast cancer, showing high levels of primary and adjuvant treatment, patients were more likely to die of causes other than breast cancer. Performance status and comorbidity tools showed prognostic and discriminatory potential in this population supporting their use in treatment decision making. CALE showed the most potential to improve treatment decisions but requires validation in this population to improve prognostic accuracy.     

Biopsia selectiva de ganglio centinela en cáncer de mama, ¿está justificada la espera al resultado intraoperatorio?

IntroductionIn our institution, the study of selective sentinel node biopsy (SLNB) is performed intraoperatively. The main objective of our study is to know the proportion of patients who benefits from the waiting of the results of SLNB.MethodsA retrospective analysis of patients operated on our center between January 1 st, 2018 and June 30, 2019 was carried out. We included women diagnosed with T1–T2 tumors, treated by lumpectomy and SLNB studied using OSNA method.ResultsOur study included 149 women. There were not statistically significant differences in terms of demographic data between the group treated with axillary lymph node dissection (ALND) and exclusively SLNB group. After analysis of SLN intraoperatively, there were performed 18 axillary lymphadenectomies. Only in six of these 18 cases, three or more sentinel nodes were founded. The location of the tumor, the presence of lymphovascular permeation and the total tumor load (TTL) showed statistically significant differences between groups. Only the TTL was established as the independent factor of the need for ALND.ConclusionsObtaining a deferred result of the SLNB allowed reducing the time of anesthesia and occupation of the operating room, since in a high percentage of cases an additional procedure is not performed.     

Interpretation,pitfalls of biomarkers in diagnosis of invasive fungal diseases

BackgroundInvasive Fungal Diseases (IFD), account for high morbidity and mortality in immunocompromised and seriously ill patients worldwide. Early, faster and accurate diagnosis with timely and appropriate patient management is critical for improved patient outcome and antifungal stewardship. Clinical/radiological presentations in IFD are non-specific and microscopy/culture based tests have low sensitivity and long turnaround time. Biomarkers have clinical utility for diagnosing IFD but their interpretation is not straight forward.ObjectivesThis review discusses the salient characteristics, clinical usefulness and limitations of common biomarkers such as Galactomannan (GM), 1–3, β D glucan (βDG), mannan, anti-mannan antibody (Mn/antiMn), Cryptococcal antigen test (CrAg), Nucleic Acid Amplification (NAA) tests and next generation sequencing for diagnosing IFD.ContentsFungal biomarkers are useful adjuncts as screening and diagnostic tools for IFD and are much more suited for ‘ruling out’ rather than ‘ruling in’ disease. GM, NAA tests are promising biomarkers for screening of invasive Aspergillosis in high risk asymptomatic patients who are not on antifungal therapy and for diagnosis of breakthrough infections in symptomatic patients. 1–3, β D glucan has limitations both as a ‘rule in’ and ‘rule out’ test and is useful in only specific clinical settings. Two consecutive positive 1-3-βDG tests or combined positivity with GM increases its specificity. Mn/antiMn, T2Candida nano diagnostic panel are promising candidates for diagnosing invasive candidiasis. Combining two or more biomarkers improves the sensitivity for prompt initiation of antifungal therapy and the negative predictive value for suspension of empirical treatment.Serum CrAg test is a good ‘rule in’ rather than a ‘rule out’ test in immunocompetent patients but has good diagnostic accuracy in immunocompromised patients. Detection of single nucleotide polymorphisms by next generation sequencing is useful for fungal characterization and identification of host determinants responsible for increased susceptibility to fungal infections but is still in experimental stages.     

基于超声影像组学的乳腺癌预测模型的诊断性能研究

目的评估并比较基于不同机器学习算法建立的乳腺癌超声影像组学预测模型的诊断性能。 方法回顾性收集2017年1月至2019年4月就诊皖南医学院第一附属医院、有明确病理结果的乳腺肿块病例828例，以2018年8月31日为节点将其分为训练集（526例）和验证集（302例），提取肿块的超声影像组学特征并进行特征筛选，运用k最近邻（kNN）、逻辑回归（LR）、朴素贝叶斯（NB）、随机森林（RF）和支持向量机（SVM）5种机器学习算法分别建立预测模型，使用重复交叉验证方法做内部验证，计算比较各模型的敏感度、特异度、阳性预测值（PPV）和阴性预测值（NPV），并实施外部验证，绘制ROC曲线并比较ROC曲线下面积（AUC）以评价模型的鉴别诊断性能，绘制校准曲线评价模型校准度。 结果从提取的109个影像组学特征中筛选出19个特征建立了5种机器学习算法模型。在内部验证中，5种模型的敏感度、特异度、PPV、NPV比较，总体差异均有统计学意义（P均＜0.001）。LR模型的特异度、PPV、NPV中位数分别为0.769、0.816、0.778，3项指标均高于其他4种模型；敏感度中位数为0.824，高于kNN、RF和SVM模型。此外，SVM模型的特异度、PPV、NPV中位数分别为0.706、0.774、0.759，虽均低于LR模型，但均高于其他3种模型。在外部验证中，LR、SVM、RF、kNN和NB的AUC依次为0.890、0.832、0.821、0.746和0.703，其中LR与SVM的AUC差异有统计学意义（P=0.012）；此外，各模型在校准性能上表现并不一致，LR和SVM模型的校准曲线显示乳腺癌实际概率与预测概率之间的一致性较好。 结论以超声影像组学特征为基础，运用不同机器学习算法建立的乳腺癌超声预测模型，均表现出较高的诊断性能，其中LR模型表现最为突出；选择合适的机器学习算法有助于进一步提高预测模型的诊断性能，提供更加准确的量化预测结果。